{"id":"W4405794460","doi":"10.5267/j.uscm.2024.10.015","title":"Fostering poverty reduction through ultra-microfinance interventions for agricultural MSES in Indonesia: The role of business size and gender","year":2024,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microfinance; Poverty reduction; Psychological intervention; Poverty; Business; Agriculture; Reduction (mathematics); Economics; Economic growth; Psychology; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004513173,0.0001757118,0.0003061411,0.0001463404,0.0001400676,0.00008036832,0.0001999506,0.00007722687,0.0000294789],"category_scores_gemma":[0.00003041695,0.0001450553,0.0001444802,0.0005674161,0.00006999051,0.0002969868,0.0002262869,0.000108063,0.000009468846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001311679,"about_ca_system_score_gemma":0.000009255464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004003562,"about_ca_topic_score_gemma":0.00004225663,"domain_scores_codex":[0.9986399,0.00001636427,0.00059434,0.0004364916,0.00004241423,0.0002705229],"domain_scores_gemma":[0.9995036,0.00006761985,0.0001680615,0.0002097744,0.00003543567,0.00001554261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001032583,0.0002293192,0.005356845,0.0030925,0.000153544,0.00001206438,0.007274341,0.0008079759,0.006809338,0.9289149,0.003273686,0.04397224],"study_design_scores_gemma":[0.001924282,0.0001917281,0.2797629,0.002021488,0.00009323758,0.00003706988,0.007363887,0.001565794,0.004344193,0.5588332,0.1428463,0.001015995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7850701,0.1090623,0.06473992,0.007822244,0.002624041,0.004582173,0.0006384592,0.0001330947,0.02532763],"genre_scores_gemma":[0.9933228,0.004190339,0.001124125,0.00009709637,0.00009741532,0.0002239925,0.00003201601,0.00001936767,0.0008928266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3700817,"threshold_uncertainty_score":0.5915183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0413948871223764,"score_gpt":0.2604668338553142,"score_spread":0.2190719467329378,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}